XLSTAT: Kernel density estimation in Excel

 

Dataset for Example

The attached dataset contains height measurements (in cm) for 1,000 individuals, categorized by gender.
Below is an excerpt for illustration:

The objective is to analyze the distribution of height within this population, with a focus on differences by gender. 

 

Setting Up

• Open XLSTAT.

• Click on the Describing data menu and select the Kernel density estimation feature.

• The Kernel density estimation dialog box appears.

In the General tab:

• Select the HEIGHT column for analysis.

• Choose SEX in the Subsamples segment to analyze by gender.

• Select the Epanechnikov Kernel.

• Choose the Silverman (1) method for Bandwidth.

In the Charts tab:

• Activate "All series on one chart" for comparison.

• Click on the OK button to launch the computations.

• The results are displayed on a new Excel sheet.

 

Interpreting the Results

Explore the XLSTAT chart below, showcasing density curves and histograms for the "HEIGHT" variable among male and female athletes.

Kernel density estimation creates a smooth curve that highlights data distribution. Analyzing the curves shows that women peak around 170cm and men around 180cm, indicating that athletic men are generally taller. The men's curve also extends beyond the women's, confirming this height disparity.